In recent years, information on the World Wide Web has grown drastically and is continuing to do so at an ever increasing rate. The prevalence of social media culture has resulted in the digitization of all aspects of lives (i.e. from conversations to celebrations). In other words, human lives have largely become synonymous with the information we consume and share on the Web. Today's man is surrounded by a plethora of information of various kinds in his disparate digital devices. Ironically, the time slice devoted for consumption of a given piece of information is decreasing by the day. Therefore, the need for concise and meaningful information presentation has become critical.
Undoubtedly, text constitutes the most abundant form of information on the Web. However, the structure of text on the Web can vary from extremely un-syntactical (e.g. tags or short form sentences) to very structured (e.g. well written and edited articles). Of late, tag-clouds have gained significance as a way to visualize structured as well as unstructured text. A tag-cloud is a visual depiction of the word content of a document. A tag-cloud can provide a quick word-content summary of large documents, collections, or tag-sets. It can be constructed by tag-frequencies or derived from an ordered tag-set by using tag-weights. An appealing aspect of tag-clouds is the presentation of the relative emphasis or importance of different words or concepts in a seemingly simple manner that a human eye can quickly discern (in contrast to listing numeric weights against different words).
Prior art in generating layouts of tag-clouds for visualization limits the shape of tag layouts or does not preserve the ordering of the set of tags. In addition, prior art for generating tag layouts can result in layouts with tags repeated to fill the space, or omitted due to lack of space, described by the shape instead of scaling the tags or the shapes to achieve a good fit.